Experiences on model based disclosure limitation

Luisa Franconi, Alessandra Capobianchi, Silvia Polettini and Giovanni Seri
Istat, Metodologia di base per la produzione statistica, Via C. Balbo 16, 00184 Roma, Italy

Abstract.
National statistical institutes routinely apply imputation methods based on statistical models to survey nonresponses. This area of research is very important because it is at the basis of the production of economic data which are as accurate as possible. The idea is to take stock of the experiences gathered in the field of imputation methodology and to try to bridge the gap between this area of research and statistical disclosure limitation. In this paper we review our experiences on model based disclosure limitation techniques. In general, these techniques substitute the observed value of a certain variable with the estimated value via a statistical model. In particular, we discuss the problems encountered and the possible solutions found with two different models: a regression tree model for a categorical variable and a hierarchical model for a continuous variable.

Keywords:
Business microdata, confidentiality, hierarchical models, regression trees

Email addresses for correspondence:
Luisa Franconi
Alessandra Capobianchi
Silvia Polettini
Giovanni Seri